Research on Express Demand Problem Based on Analytic Hierarchy Process, Entropy Weight Method and ARIMA Time Series

Kecheng Yang; Zhoukai Cheng; Tao Tao

doi:10.54097/hset.v70i.12150

Authors

Kecheng Yang
Zhoukai Cheng
Tao Tao

DOI:

https://doi.org/10.54097/hset.v70i.12150

Keywords:

Analytic hierarchy process, Entropy weight method, ARIMA time series.

Abstract

Under the background of rapid development of express industry, this article establishes the evaluation model of station city importance and the forecast model of express transport volume by means of analytic hierarchy process, entropy weight method and ARIMA time series model, which has strong practical significance. Firstly, this article preprocess the data to get the daily receipt and shipment of each city. Then, seven indexes are selected as the comprehensive evaluation indexes of each station city, a comprehensive evaluation system based on analytic hierarchy process and entropy weight method is constructed, and the evaluation model of the importance degree of each station city is established. Considering that the number of express delivery varies greatly and irregularly, this article chooses the ARIMA time series analysis model, and determine the coefficient of the ARIMA time series analysis model through the ACF diagram and the PACF diagram, and plug the data into the prediction model to obtain the prediction result of the number of express transportation between stations and cities.

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